AUTHOR=Pootakham Wirulda , Ruang-Areerate Panthita , Jomchai Nukoon , Sonthirod Chutima , Sangsrakru Duangjai , Yoocha Thippawan , Theerawattanasuk Kanikar , Nirapathpongporn Kanlaya , Romruensukharom Phayao , Tragoonrung Somvong , Tangphatsornruang Sithichoke TITLE=Construction of a high-density integrated genetic linkage map of rubber tree (Hevea brasiliensis) using genotyping-by-sequencing (GBS) JOURNAL=Frontiers in Plant Science VOLUME=6 YEAR=2015 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2015.00367 DOI=10.3389/fpls.2015.00367 ISSN=1664-462X ABSTRACT=

Construction of linkage maps is crucial for genetic studies and marker-assisted breeding programs. Recent advances in next generation sequencing technologies allow for the generation of high-density linkage maps, especially in non-model species lacking extensive genomic resources. Here, we constructed a high-density integrated genetic linkage map of rubber tree (Hevea brasiliensis), the sole commercial producer of high-quality natural rubber. We applied a genotyping-by-sequencing (GBS) technique to simultaneously discover and genotype single nucleotide polymorphism (SNP) markers in two rubber tree populations. A total of 21,353 single nucleotide substitutions were identified, 55% of which represented transition events. GBS-based genetic maps of populations P and C comprised 1704 and 1719 markers and encompassed 2041 cM and 1874 cM, respectively. The average marker densities of these two maps were one SNP in 1.23–1.25 cM. A total of 1114 shared SNP markers were used to merge the two component maps. An integrated linkage map consisted of 2321 markers and spanned the cumulative length of 2052 cM. The composite map showed a substantial improvement in marker density, with one SNP marker in every 0.89 cM. To our knowledge, this is the most saturated genetic map in rubber tree to date. This integrated map allowed us to anchor 28,965 contigs, covering 135 Mb or 12% of the published rubber tree genome. We demonstrated that GBS is a robust and cost-effective approach for generating a common set of genome-wide SNP data suitable for constructing integrated linkage maps from multiple populations in a highly heterozygous agricultural species.